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<div class="header">
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<a href="#pub-types">Public 类型</a> &#124;
<a href="#pub-methods">Public 成员函数</a> &#124;
<a href="#pro-methods">Protected 成员函数</a> &#124;
<a href="#pro-attribs">Protected 属性</a> &#124;
<a href="#pri-methods">Private 成员函数</a> &#124;
<a href="#pri-attribs">Private 属性</a> &#124;
<a href="classpcl_1_1registration_1_1_correspondence_rejector_poly-members.html">所有成员列表</a>  </div>
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<div class="title">pcl::registration::CorrespondenceRejectorPoly&lt; SourceT, TargetT &gt; 模板类 参考</div>  </div>
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<p><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html" title="CorrespondenceRejectorPoly implements a correspondence rejection method that exploits low-level and p...">CorrespondenceRejectorPoly</a> implements a correspondence rejection method that exploits low-level and pose-invariant geometric constraints between two point sets by forming virtual polygons of a user-specifiable cardinality on each model using the input correspondences. These polygons are then checked in a pose-invariant manner (i.e. the side lengths must be approximately equal), and rejection is performed by thresholding these edge lengths.  
 <a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#details">更多...</a></p>

<p><code>#include &lt;<a class="el" href="correspondence__rejection__poly_8h_source.html">correspondence_rejection_poly.h</a>&gt;</code></p>
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类 pcl::registration::CorrespondenceRejectorPoly&lt; SourceT, TargetT &gt; 继承关系图:</div>
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  <img src="classpcl_1_1registration_1_1_correspondence_rejector_poly.png" usemap="#pcl::registration::CorrespondenceRejectorPoly_3C_20SourceT_2C_20TargetT_20_3E_map" alt=""/>
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<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-types"></a>
Public 类型</h2></td></tr>
<tr class="memitem:a2f46855836ad7ab2e2fdcfb00738ebe3"><td class="memItemLeft" align="right" valign="top"><a id="a2f46855836ad7ab2e2fdcfb00738ebe3"></a>
typedef boost::shared_ptr&lt; <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html">CorrespondenceRejectorPoly</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>Ptr</b></td></tr>
<tr class="separator:a2f46855836ad7ab2e2fdcfb00738ebe3"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a42d9b588b755dafc4e1ca0499b1c8d33"><td class="memItemLeft" align="right" valign="top"><a id="a42d9b588b755dafc4e1ca0499b1c8d33"></a>
typedef boost::shared_ptr&lt; const <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html">CorrespondenceRejectorPoly</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>ConstPtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; SourceT &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudSource</b></td></tr>
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typedef PointCloudSource::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudSourcePtr</b></td></tr>
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typedef PointCloudSource::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudSourceConstPtr</b></td></tr>
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<tr class="memitem:a55c84948c660f387cfc8da2ea99c40cb"><td class="memItemLeft" align="right" valign="top"><a id="a55c84948c660f387cfc8da2ea99c40cb"></a>
typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; TargetT &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudTarget</b></td></tr>
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typedef PointCloudTarget::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudTargetPtr</b></td></tr>
<tr class="separator:ac89b2bfa80010ccae94e323e4dd07c00"><td class="memSeparator" colspan="2">&#160;</td></tr>
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typedef PointCloudTarget::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudTargetConstPtr</b></td></tr>
<tr class="separator:a48696db05f0fb7d542552c6eabf5869a"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_types_classpcl_1_1registration_1_1_correspondence_rejector"><td colspan="2" onclick="javascript:toggleInherit('pub_types_classpcl_1_1registration_1_1_correspondence_rejector')"><img src="closed.png" alt="-"/>&#160;Public 类型 继承自 <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector.html">pcl::registration::CorrespondenceRejector</a></td></tr>
<tr class="memitem:a192578d5c6faa199b6137f7052ebe3bd inherit pub_types_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memItemLeft" align="right" valign="top"><a id="a192578d5c6faa199b6137f7052ebe3bd"></a>
typedef boost::shared_ptr&lt; <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector.html">CorrespondenceRejector</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>Ptr</b></td></tr>
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<tr class="memitem:a364a36b29c665856a1819d7a42cf5154 inherit pub_types_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memItemLeft" align="right" valign="top"><a id="a364a36b29c665856a1819d7a42cf5154"></a>
typedef boost::shared_ptr&lt; const <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector.html">CorrespondenceRejector</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>ConstPtr</b></td></tr>
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</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public 成员函数</h2></td></tr>
<tr class="memitem:aadfc2c6fc8fb83f346d06cf47f49b702"><td class="memItemLeft" align="right" valign="top"><a id="aadfc2c6fc8fb83f346d06cf47f49b702"></a>
&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#aadfc2c6fc8fb83f346d06cf47f49b702">CorrespondenceRejectorPoly</a> ()</td></tr>
<tr class="memdesc:aadfc2c6fc8fb83f346d06cf47f49b702"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty constructor <br /></td></tr>
<tr class="separator:aadfc2c6fc8fb83f346d06cf47f49b702"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab9dd0c9b233328c85803229009be093e"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#ab9dd0c9b233328c85803229009be093e">getRemainingCorrespondences</a> (const pcl::Correspondences &amp;original_correspondences, pcl::Correspondences &amp;remaining_correspondences)</td></tr>
<tr class="memdesc:ab9dd0c9b233328c85803229009be093e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a list of valid correspondences after rejection from the original set of correspondences.  <a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#ab9dd0c9b233328c85803229009be093e">更多...</a><br /></td></tr>
<tr class="separator:ab9dd0c9b233328c85803229009be093e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:acc2f89f5758f9de93be9e2daa27af68b"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#acc2f89f5758f9de93be9e2daa27af68b">setInputSource</a> (const PointCloudSourceConstPtr &amp;cloud)</td></tr>
<tr class="memdesc:acc2f89f5758f9de93be9e2daa27af68b"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a source point cloud dataset (must contain XYZ data!), used to compute the correspondence distance.  <a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#acc2f89f5758f9de93be9e2daa27af68b">更多...</a><br /></td></tr>
<tr class="separator:acc2f89f5758f9de93be9e2daa27af68b"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad276f9b13f87fb0a43cbaa12bc83da75"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#ad276f9b13f87fb0a43cbaa12bc83da75">setInputCloud</a> (const PointCloudSourceConstPtr &amp;cloud)</td></tr>
<tr class="memdesc:ad276f9b13f87fb0a43cbaa12bc83da75"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a source point cloud dataset (must contain XYZ data!), used to compute the correspondence distance.  <a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#ad276f9b13f87fb0a43cbaa12bc83da75">更多...</a><br /></td></tr>
<tr class="separator:ad276f9b13f87fb0a43cbaa12bc83da75"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac1fb853163ad7d9bfb3cfa2629bc5e5e"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#ac1fb853163ad7d9bfb3cfa2629bc5e5e">setInputTarget</a> (const PointCloudTargetConstPtr &amp;target)</td></tr>
<tr class="memdesc:ac1fb853163ad7d9bfb3cfa2629bc5e5e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a target point cloud dataset (must contain XYZ data!), used to compute the correspondence distance.  <a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#ac1fb853163ad7d9bfb3cfa2629bc5e5e">更多...</a><br /></td></tr>
<tr class="separator:ac1fb853163ad7d9bfb3cfa2629bc5e5e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4a73f902b8554048c5c7356a6e5e94d7"><td class="memItemLeft" align="right" valign="top"><a id="a4a73f902b8554048c5c7356a6e5e94d7"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a4a73f902b8554048c5c7356a6e5e94d7">requiresSourcePoints</a> () const</td></tr>
<tr class="memdesc:a4a73f902b8554048c5c7356a6e5e94d7"><td class="mdescLeft">&#160;</td><td class="mdescRight">See if this rejector requires source points <br /></td></tr>
<tr class="separator:a4a73f902b8554048c5c7356a6e5e94d7"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad58030d5d71f4a11c8ea4a6a453f5958"><td class="memItemLeft" align="right" valign="top"><a id="ad58030d5d71f4a11c8ea4a6a453f5958"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#ad58030d5d71f4a11c8ea4a6a453f5958">setSourcePoints</a> (pcl::PCLPointCloud2::ConstPtr cloud2)</td></tr>
<tr class="memdesc:ad58030d5d71f4a11c8ea4a6a453f5958"><td class="mdescLeft">&#160;</td><td class="mdescRight">Blob method for setting the source cloud <br /></td></tr>
<tr class="separator:ad58030d5d71f4a11c8ea4a6a453f5958"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a140261c30a95619e33d94b4d44373947"><td class="memItemLeft" align="right" valign="top"><a id="a140261c30a95619e33d94b4d44373947"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a140261c30a95619e33d94b4d44373947">requiresTargetPoints</a> () const</td></tr>
<tr class="memdesc:a140261c30a95619e33d94b4d44373947"><td class="mdescLeft">&#160;</td><td class="mdescRight">See if this rejector requires a target cloud <br /></td></tr>
<tr class="separator:a140261c30a95619e33d94b4d44373947"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8bafb7d0b19e66ad4bf51d5b6a148d64"><td class="memItemLeft" align="right" valign="top"><a id="a8bafb7d0b19e66ad4bf51d5b6a148d64"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a8bafb7d0b19e66ad4bf51d5b6a148d64">setTargetPoints</a> (pcl::PCLPointCloud2::ConstPtr cloud2)</td></tr>
<tr class="memdesc:a8bafb7d0b19e66ad4bf51d5b6a148d64"><td class="mdescLeft">&#160;</td><td class="mdescRight">Method for setting the target cloud <br /></td></tr>
<tr class="separator:a8bafb7d0b19e66ad4bf51d5b6a148d64"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7ff2c8b9c339f3a2002903445c571ebc"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a7ff2c8b9c339f3a2002903445c571ebc">setCardinality</a> (int cardinality)</td></tr>
<tr class="memdesc:a7ff2c8b9c339f3a2002903445c571ebc"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the polygon cardinality  <a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a7ff2c8b9c339f3a2002903445c571ebc">更多...</a><br /></td></tr>
<tr class="separator:a7ff2c8b9c339f3a2002903445c571ebc"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af51b83c930c0eded4255f0b125e0d264"><td class="memItemLeft" align="right" valign="top">int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#af51b83c930c0eded4255f0b125e0d264">getCardinality</a> ()</td></tr>
<tr class="memdesc:af51b83c930c0eded4255f0b125e0d264"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the polygon cardinality  <a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#af51b83c930c0eded4255f0b125e0d264">更多...</a><br /></td></tr>
<tr class="separator:af51b83c930c0eded4255f0b125e0d264"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a82e96a355a8bda9f912ac4c1a1c5dc6e"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a82e96a355a8bda9f912ac4c1a1c5dc6e">setSimilarityThreshold</a> (float similarity_threshold)</td></tr>
<tr class="memdesc:a82e96a355a8bda9f912ac4c1a1c5dc6e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the similarity threshold in [0,1[ between edge lengths, where 1 is a perfect match  <a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a82e96a355a8bda9f912ac4c1a1c5dc6e">更多...</a><br /></td></tr>
<tr class="separator:a82e96a355a8bda9f912ac4c1a1c5dc6e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a5bba3105e4e30c6892b89d381f190898"><td class="memItemLeft" align="right" valign="top">float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a5bba3105e4e30c6892b89d381f190898">getSimilarityThreshold</a> ()</td></tr>
<tr class="memdesc:a5bba3105e4e30c6892b89d381f190898"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the similarity threshold between edge lengths  <a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a5bba3105e4e30c6892b89d381f190898">更多...</a><br /></td></tr>
<tr class="separator:a5bba3105e4e30c6892b89d381f190898"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a930c9e70a639fbe1d4e4228cd1dfc57b"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a930c9e70a639fbe1d4e4228cd1dfc57b">setIterations</a> (int iterations)</td></tr>
<tr class="memdesc:a930c9e70a639fbe1d4e4228cd1dfc57b"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the number of iterations  <a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a930c9e70a639fbe1d4e4228cd1dfc57b">更多...</a><br /></td></tr>
<tr class="separator:a930c9e70a639fbe1d4e4228cd1dfc57b"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3b23f465b997d88b0b628e646f9dd3a3"><td class="memItemLeft" align="right" valign="top">int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a3b23f465b997d88b0b628e646f9dd3a3">getIterations</a> ()</td></tr>
<tr class="memdesc:a3b23f465b997d88b0b628e646f9dd3a3"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the number of iterations  <a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a3b23f465b997d88b0b628e646f9dd3a3">更多...</a><br /></td></tr>
<tr class="separator:a3b23f465b997d88b0b628e646f9dd3a3"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a1b0cbb221e66b90cccae29cf84a64147"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a1b0cbb221e66b90cccae29cf84a64147">thresholdPolygon</a> (const pcl::Correspondences &amp;corr, const std::vector&lt; int &gt; &amp;idx)</td></tr>
<tr class="memdesc:a1b0cbb221e66b90cccae29cf84a64147"><td class="mdescLeft">&#160;</td><td class="mdescRight">Polygonal rejection of a single polygon, indexed by a subset of correspondences  <a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a1b0cbb221e66b90cccae29cf84a64147">更多...</a><br /></td></tr>
<tr class="separator:a1b0cbb221e66b90cccae29cf84a64147"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4e889746bd0466f9b48a92a46fb39e3e"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a4e889746bd0466f9b48a92a46fb39e3e">thresholdPolygon</a> (const std::vector&lt; int &gt; &amp;source_indices, const std::vector&lt; int &gt; &amp;target_indices)</td></tr>
<tr class="memdesc:a4e889746bd0466f9b48a92a46fb39e3e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Polygonal rejection of a single polygon, indexed by two point index vectors  <a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a4e889746bd0466f9b48a92a46fb39e3e">更多...</a><br /></td></tr>
<tr class="separator:a4e889746bd0466f9b48a92a46fb39e3e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classpcl_1_1registration_1_1_correspondence_rejector')"><img src="closed.png" alt="-"/>&#160;Public 成员函数 继承自 <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector.html">pcl::registration::CorrespondenceRejector</a></td></tr>
<tr class="memitem:aece0e22dd156eaacff20b45069036483 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memItemLeft" align="right" valign="top"><a id="aece0e22dd156eaacff20b45069036483"></a>
&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector.html#aece0e22dd156eaacff20b45069036483">CorrespondenceRejector</a> ()</td></tr>
<tr class="memdesc:aece0e22dd156eaacff20b45069036483 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty constructor. <br /></td></tr>
<tr class="separator:aece0e22dd156eaacff20b45069036483 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6cbaada1584e194daaad3fd0c2d4aee8 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memItemLeft" align="right" valign="top"><a id="a6cbaada1584e194daaad3fd0c2d4aee8"></a>
virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector.html#a6cbaada1584e194daaad3fd0c2d4aee8">~CorrespondenceRejector</a> ()</td></tr>
<tr class="memdesc:a6cbaada1584e194daaad3fd0c2d4aee8 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty destructor. <br /></td></tr>
<tr class="separator:a6cbaada1584e194daaad3fd0c2d4aee8 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af69c08f02cc1a3f69920f73f1664f0d8 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector.html#af69c08f02cc1a3f69920f73f1664f0d8">setInputCorrespondences</a> (const CorrespondencesConstPtr &amp;correspondences)</td></tr>
<tr class="memdesc:af69c08f02cc1a3f69920f73f1664f0d8 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the vector of the input correspondences.  <a href="classpcl_1_1registration_1_1_correspondence_rejector.html#af69c08f02cc1a3f69920f73f1664f0d8">更多...</a><br /></td></tr>
<tr class="separator:af69c08f02cc1a3f69920f73f1664f0d8 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae43d54dc28964e8df4ab05b74c3b7135 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memItemLeft" align="right" valign="top">CorrespondencesConstPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector.html#ae43d54dc28964e8df4ab05b74c3b7135">getInputCorrespondences</a> ()</td></tr>
<tr class="memdesc:ae43d54dc28964e8df4ab05b74c3b7135 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the vector of the input correspondences.  <a href="classpcl_1_1registration_1_1_correspondence_rejector.html#ae43d54dc28964e8df4ab05b74c3b7135">更多...</a><br /></td></tr>
<tr class="separator:ae43d54dc28964e8df4ab05b74c3b7135 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a72c90f3fb93739b0366d3528cf7d502f inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector.html#a72c90f3fb93739b0366d3528cf7d502f">getCorrespondences</a> (pcl::Correspondences &amp;correspondences)</td></tr>
<tr class="memdesc:a72c90f3fb93739b0366d3528cf7d502f inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="mdescLeft">&#160;</td><td class="mdescRight">Run correspondence rejection  <a href="classpcl_1_1registration_1_1_correspondence_rejector.html#a72c90f3fb93739b0366d3528cf7d502f">更多...</a><br /></td></tr>
<tr class="separator:a72c90f3fb93739b0366d3528cf7d502f inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6a1c8dff3bcce8f99ec98b9982838ffc inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector.html#a6a1c8dff3bcce8f99ec98b9982838ffc">getRejectedQueryIndices</a> (const pcl::Correspondences &amp;correspondences, std::vector&lt; int &gt; &amp;indices)</td></tr>
<tr class="memdesc:a6a1c8dff3bcce8f99ec98b9982838ffc inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="mdescLeft">&#160;</td><td class="mdescRight">Determine the indices of query points of correspondences that have been rejected, i.e., the difference between the input correspondences (set via <em>setInputCorrespondences</em>) and the given correspondence vector.  <a href="classpcl_1_1registration_1_1_correspondence_rejector.html#a6a1c8dff3bcce8f99ec98b9982838ffc">更多...</a><br /></td></tr>
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<tr class="memitem:aa5996af869d7aaa6b8b8dc156038dd3f inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memItemLeft" align="right" valign="top"><a id="aa5996af869d7aaa6b8b8dc156038dd3f"></a>
const std::string &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector.html#aa5996af869d7aaa6b8b8dc156038dd3f">getClassName</a> () const</td></tr>
<tr class="memdesc:aa5996af869d7aaa6b8b8dc156038dd3f inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a string representation of the name of this class. <br /></td></tr>
<tr class="separator:aa5996af869d7aaa6b8b8dc156038dd3f inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a08f07ed59490ee2c5d01a99d5589e306 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memItemLeft" align="right" valign="top"><a id="a08f07ed59490ee2c5d01a99d5589e306"></a>
virtual bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector.html#a08f07ed59490ee2c5d01a99d5589e306">requiresSourceNormals</a> () const</td></tr>
<tr class="memdesc:a08f07ed59490ee2c5d01a99d5589e306 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="mdescLeft">&#160;</td><td class="mdescRight">See if this rejector requires source normals <br /></td></tr>
<tr class="separator:a08f07ed59490ee2c5d01a99d5589e306 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2f61f392a8d0c3da5502949cb22bba7d inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memItemLeft" align="right" valign="top"><a id="a2f61f392a8d0c3da5502949cb22bba7d"></a>
virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector.html#a2f61f392a8d0c3da5502949cb22bba7d">setSourceNormals</a> (pcl::PCLPointCloud2::ConstPtr)</td></tr>
<tr class="memdesc:a2f61f392a8d0c3da5502949cb22bba7d inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="mdescLeft">&#160;</td><td class="mdescRight">Abstract method for setting the source normals <br /></td></tr>
<tr class="separator:a2f61f392a8d0c3da5502949cb22bba7d inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab3afeffa725f643d1ebc3c0545ea05be inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memItemLeft" align="right" valign="top"><a id="ab3afeffa725f643d1ebc3c0545ea05be"></a>
virtual bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector.html#ab3afeffa725f643d1ebc3c0545ea05be">requiresTargetNormals</a> () const</td></tr>
<tr class="memdesc:ab3afeffa725f643d1ebc3c0545ea05be inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="mdescLeft">&#160;</td><td class="mdescRight">See if this rejector requires target normals <br /></td></tr>
<tr class="separator:ab3afeffa725f643d1ebc3c0545ea05be inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4bbb67f5066c674eba95b440bb4fd03a inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memItemLeft" align="right" valign="top"><a id="a4bbb67f5066c674eba95b440bb4fd03a"></a>
virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector.html#a4bbb67f5066c674eba95b440bb4fd03a">setTargetNormals</a> (pcl::PCLPointCloud2::ConstPtr)</td></tr>
<tr class="memdesc:a4bbb67f5066c674eba95b440bb4fd03a inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="mdescLeft">&#160;</td><td class="mdescRight">Abstract method for setting the target normals <br /></td></tr>
<tr class="separator:a4bbb67f5066c674eba95b440bb4fd03a inherit pub_methods_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pro-methods"></a>
Protected 成员函数</h2></td></tr>
<tr class="memitem:a72457989897b8ae21c84db797998c8e0"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a72457989897b8ae21c84db797998c8e0">applyRejection</a> (pcl::Correspondences &amp;correspondences)</td></tr>
<tr class="memdesc:a72457989897b8ae21c84db797998c8e0"><td class="mdescLeft">&#160;</td><td class="mdescRight">Apply the rejection algorithm.  <a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a72457989897b8ae21c84db797998c8e0">更多...</a><br /></td></tr>
<tr class="separator:a72457989897b8ae21c84db797998c8e0"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:adc6fa46eff68234bc35733343dce9d53"><td class="memItemLeft" align="right" valign="top">std::vector&lt; int &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#adc6fa46eff68234bc35733343dce9d53">getUniqueRandomIndices</a> (int n, int k)</td></tr>
<tr class="memdesc:adc6fa46eff68234bc35733343dce9d53"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get k unique random indices in range {0,...,n-1} (sampling without replacement)  <a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#adc6fa46eff68234bc35733343dce9d53">更多...</a><br /></td></tr>
<tr class="separator:adc6fa46eff68234bc35733343dce9d53"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a382b6d87c8e6d2d0750214abd67f26a5"><td class="memItemLeft" align="right" valign="top">float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a382b6d87c8e6d2d0750214abd67f26a5">computeSquaredDistance</a> (const SourceT &amp;p1, const TargetT &amp;p2)</td></tr>
<tr class="memdesc:a382b6d87c8e6d2d0750214abd67f26a5"><td class="mdescLeft">&#160;</td><td class="mdescRight">Squared Euclidean distance between two points using the members x, y and z  <a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a382b6d87c8e6d2d0750214abd67f26a5">更多...</a><br /></td></tr>
<tr class="separator:a382b6d87c8e6d2d0750214abd67f26a5"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa6d7f1b7dfe41620829a2c957b4229e1"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#aa6d7f1b7dfe41620829a2c957b4229e1">thresholdEdgeLength</a> (int index_query_1, int index_query_2, int index_match_1, int index_match_2, float simsq)</td></tr>
<tr class="memdesc:aa6d7f1b7dfe41620829a2c957b4229e1"><td class="mdescLeft">&#160;</td><td class="mdescRight"><a class="el" href="classpcl_1_1_edge.html">Edge</a> length similarity thresholding  <a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#aa6d7f1b7dfe41620829a2c957b4229e1">更多...</a><br /></td></tr>
<tr class="separator:aa6d7f1b7dfe41620829a2c957b4229e1"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a37fe57f588ae4c5123a68de1da641e5d"><td class="memItemLeft" align="right" valign="top">std::vector&lt; int &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a37fe57f588ae4c5123a68de1da641e5d">computeHistogram</a> (const std::vector&lt; float &gt; &amp;data, float lower, float upper, int bins)</td></tr>
<tr class="memdesc:a37fe57f588ae4c5123a68de1da641e5d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute a linear histogram. This function is equivalent to the MATLAB function <b>histc</b>, with the edges set as follows: <b> lower:(upper-lower)/bins:upper </b>  <a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a37fe57f588ae4c5123a68de1da641e5d">更多...</a><br /></td></tr>
<tr class="separator:a37fe57f588ae4c5123a68de1da641e5d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a86918596b556ca1626f2a55640ae971e"><td class="memItemLeft" align="right" valign="top">int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a86918596b556ca1626f2a55640ae971e">findThresholdOtsu</a> (const std::vector&lt; int &gt; &amp;histogram)</td></tr>
<tr class="memdesc:a86918596b556ca1626f2a55640ae971e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Find the optimal value for binary histogram thresholding using Otsu's method  <a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a86918596b556ca1626f2a55640ae971e">更多...</a><br /></td></tr>
<tr class="separator:a86918596b556ca1626f2a55640ae971e"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pro-attribs"></a>
Protected 属性</h2></td></tr>
<tr class="memitem:a5575ac6cf13ce0c4054ba040afde56b8"><td class="memItemLeft" align="right" valign="top"><a id="a5575ac6cf13ce0c4054ba040afde56b8"></a>
PointCloudSourceConstPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a5575ac6cf13ce0c4054ba040afde56b8">input_</a></td></tr>
<tr class="memdesc:a5575ac6cf13ce0c4054ba040afde56b8"><td class="mdescLeft">&#160;</td><td class="mdescRight">The input point cloud dataset <br /></td></tr>
<tr class="separator:a5575ac6cf13ce0c4054ba040afde56b8"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:abb0f66416db785a197d534755e562f19"><td class="memItemLeft" align="right" valign="top"><a id="abb0f66416db785a197d534755e562f19"></a>
PointCloudTargetConstPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#abb0f66416db785a197d534755e562f19">target_</a></td></tr>
<tr class="memdesc:abb0f66416db785a197d534755e562f19"><td class="mdescLeft">&#160;</td><td class="mdescRight">The input point cloud dataset target <br /></td></tr>
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<tr class="memitem:aed548e72f310a9fc5a31cec68bc7777a"><td class="memItemLeft" align="right" valign="top"><a id="aed548e72f310a9fc5a31cec68bc7777a"></a>
int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#aed548e72f310a9fc5a31cec68bc7777a">iterations_</a></td></tr>
<tr class="memdesc:aed548e72f310a9fc5a31cec68bc7777a"><td class="mdescLeft">&#160;</td><td class="mdescRight">Number of iterations to run <br /></td></tr>
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int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#afa554cac284422e196653d72e502a610">cardinality_</a></td></tr>
<tr class="memdesc:afa554cac284422e196653d72e502a610"><td class="mdescLeft">&#160;</td><td class="mdescRight">The polygon cardinality used during rejection <br /></td></tr>
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float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a34b2739826ffc25631b21fcdb20b2415">similarity_threshold_</a></td></tr>
<tr class="memdesc:a34b2739826ffc25631b21fcdb20b2415"><td class="mdescLeft">&#160;</td><td class="mdescRight">Lower edge length threshold in [0,1] used for verifying polygon similarities, where 1 is a perfect match <br /></td></tr>
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float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a07a4439a78a6f833ef62be904abd7742">similarity_threshold_squared_</a></td></tr>
<tr class="memdesc:a07a4439a78a6f833ef62be904abd7742"><td class="mdescLeft">&#160;</td><td class="mdescRight">Squared value if <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a34b2739826ffc25631b21fcdb20b2415">similarity_threshold_</a>, only for internal use <br /></td></tr>
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<tr class="inherit_header pro_attribs_classpcl_1_1registration_1_1_correspondence_rejector"><td colspan="2" onclick="javascript:toggleInherit('pro_attribs_classpcl_1_1registration_1_1_correspondence_rejector')"><img src="closed.png" alt="-"/>&#160;Protected 属性 继承自 <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector.html">pcl::registration::CorrespondenceRejector</a></td></tr>
<tr class="memitem:ab97eb70d3661574301fe1f978576726d inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_rejector"><td class="memItemLeft" align="right" valign="top"><a id="ab97eb70d3661574301fe1f978576726d"></a>
std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector.html#ab97eb70d3661574301fe1f978576726d">rejection_name_</a></td></tr>
<tr class="memdesc:ab97eb70d3661574301fe1f978576726d inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_rejector"><td class="mdescLeft">&#160;</td><td class="mdescRight">The name of the rejection method. <br /></td></tr>
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CorrespondencesConstPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector.html#a74d516ca516f7421fd86a53dec1a57b1">input_correspondences_</a></td></tr>
<tr class="memdesc:a74d516ca516f7421fd86a53dec1a57b1 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_rejector"><td class="mdescLeft">&#160;</td><td class="mdescRight">The input correspondences. <br /></td></tr>
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Private 成员函数</h2></td></tr>
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const std::string &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#aa5996af869d7aaa6b8b8dc156038dd3f">getClassName</a> () const</td></tr>
<tr class="memdesc:aa5996af869d7aaa6b8b8dc156038dd3f"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a string representation of the name of this class. <br /></td></tr>
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Private 属性</h2></td></tr>
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CorrespondencesConstPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a74d516ca516f7421fd86a53dec1a57b1">input_correspondences_</a></td></tr>
<tr class="memdesc:a74d516ca516f7421fd86a53dec1a57b1"><td class="mdescLeft">&#160;</td><td class="mdescRight">The input correspondences. <br /></td></tr>
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std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#ab97eb70d3661574301fe1f978576726d">rejection_name_</a></td></tr>
<tr class="memdesc:ab97eb70d3661574301fe1f978576726d"><td class="mdescLeft">&#160;</td><td class="mdescRight">The name of the rejection method. <br /></td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">详细描述</h2>
<div class="textblock"><h3>template&lt;typename SourceT, typename TargetT&gt;<br />
class pcl::registration::CorrespondenceRejectorPoly&lt; SourceT, TargetT &gt;</h3>

<p><a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html" title="CorrespondenceRejectorPoly implements a correspondence rejection method that exploits low-level and p...">CorrespondenceRejectorPoly</a> implements a correspondence rejection method that exploits low-level and pose-invariant geometric constraints between two point sets by forming virtual polygons of a user-specifiable cardinality on each model using the input correspondences. These polygons are then checked in a pose-invariant manner (i.e. the side lengths must be approximately equal), and rejection is performed by thresholding these edge lengths. </p>
<p>If you use this in academic work, please cite:</p>
<p>A. G. Buch, D. Kraft, J.-K. Kämäräinen, H. G. Petersen and N. Krüger. Pose Estimation using Local Structure-Specific Shape and Appearance Context. International Conference on Robotics and Automation (ICRA), 2013.</p>
<dl class="section author"><dt>作者</dt><dd>Anders Glent Buch </dd></dl>
</div><h2 class="groupheader">成员函数说明</h2>
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<h2 class="memtitle"><span class="permalink"><a href="#a72457989897b8ae21c84db797998c8e0">&#9670;&nbsp;</a></span>applyRejection()</h2>

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          <td class="memname">void <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html">pcl::registration::CorrespondenceRejectorPoly</a>&lt; SourceT, TargetT &gt;::applyRejection </td>
          <td>(</td>
          <td class="paramtype">pcl::Correspondences &amp;&#160;</td>
          <td class="paramname"><em>correspondences</em></td><td>)</td>
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<p>Apply the rejection algorithm. </p>
<dl class="params"><dt>参数</dt><dd>
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    <tr><td class="paramdir">[out]</td><td class="paramname">correspondences</td><td>the set of resultant correspondences. </td></tr>
  </table>
  </dd>
</dl>

<p>实现了 <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector.html#a60dbdcf8f1005a1405dcab244a5c5608">pcl::registration::CorrespondenceRejector</a>.</p>
<div class="fragment"><div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;        {</div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;          <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#ab9dd0c9b233328c85803229009be093e">getRemainingCorrespondences</a> (*<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a74d516ca516f7421fd86a53dec1a57b1">input_correspondences_</a>, correspondences);</div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;        }</div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_rejector_poly_html_a74d516ca516f7421fd86a53dec1a57b1"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a74d516ca516f7421fd86a53dec1a57b1">pcl::registration::CorrespondenceRejectorPoly::input_correspondences_</a></div><div class="ttdeci">CorrespondencesConstPtr input_correspondences_</div><div class="ttdoc">The input correspondences.</div><div class="ttdef"><b>Definition:</b> correspondence_rejection.h:191</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_rejector_poly_html_ab9dd0c9b233328c85803229009be093e"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#ab9dd0c9b233328c85803229009be093e">pcl::registration::CorrespondenceRejectorPoly::getRemainingCorrespondences</a></div><div class="ttdeci">void getRemainingCorrespondences(const pcl::Correspondences &amp;original_correspondences, pcl::Correspondences &amp;remaining_correspondences)</div><div class="ttdoc">Get a list of valid correspondences after rejection from the original set of correspondences.</div><div class="ttdef"><b>Definition:</b> correspondence_rejection_poly.hpp:43</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a37fe57f588ae4c5123a68de1da641e5d">&#9670;&nbsp;</a></span>computeHistogram()</h2>

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          <td>(</td>
          <td class="paramtype">const std::vector&lt; float &gt; &amp;&#160;</td>
          <td class="paramname"><em>data</em>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">float&#160;</td>
          <td class="paramname"><em>lower</em>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">float&#160;</td>
          <td class="paramname"><em>upper</em>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int&#160;</td>
          <td class="paramname"><em>bins</em>&#160;</td>
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          <td>)</td>
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<p>Compute a linear histogram. This function is equivalent to the MATLAB function <b>histc</b>, with the edges set as follows: <b> lower:(upper-lower)/bins:upper </b> </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramname">data</td><td>input samples </td></tr>
    <tr><td class="paramname">lower</td><td>lower bound of input samples </td></tr>
    <tr><td class="paramname">upper</td><td>upper bound of input samples </td></tr>
    <tr><td class="paramname">bins</td><td>number of bins in output </td></tr>
  </table>
  </dd>
</dl>
<dl class="section return"><dt>返回</dt><dd>linear histogram </dd></dl>
<div class="fragment"><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;{</div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;  <span class="comment">// Result</span></div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;  std::vector&lt;int&gt; result (bins, 0);</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;  </div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;  <span class="comment">// Last index into result and increment factor from data value --&gt; index</span></div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">int</span> last_idx = bins - 1;</div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">float</span> idx_per_val = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (bins) / (upper - lower);</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;  </div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;  <span class="comment">// Accumulate</span></div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;  <span class="keywordflow">for</span> (std::vector&lt;float&gt;::const_iterator it = data.begin (); it != data.end (); ++it)</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;     ++result[ std::min (last_idx, <span class="keywordtype">int</span> ((*it)*idx_per_val)) ];</div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;  </div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;  <span class="keywordflow">return</span> (result);</div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;}</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a382b6d87c8e6d2d0750214abd67f26a5">&#9670;&nbsp;</a></span>computeSquaredDistance()</h2>

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          <td class="memname">float <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html">pcl::registration::CorrespondenceRejectorPoly</a>&lt; SourceT, TargetT &gt;::computeSquaredDistance </td>
          <td>(</td>
          <td class="paramtype">const SourceT &amp;&#160;</td>
          <td class="paramname"><em>p1</em>, </td>
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          <td class="paramname"><em>p2</em>&#160;</td>
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<p>Squared Euclidean distance between two points using the members x, y and z </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramname">p1</td><td>first point </td></tr>
    <tr><td class="paramname">p2</td><td>second point </td></tr>
  </table>
  </dd>
</dl>
<dl class="section return"><dt>返回</dt><dd>squared Euclidean distance </dd></dl>
<div class="fragment"><div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;        {</div>
<div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;          <span class="keyword">const</span> <span class="keywordtype">float</span> dx = p2.x - p1.x;</div>
<div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;          <span class="keyword">const</span> <span class="keywordtype">float</span> dy = p2.y - p1.y;</div>
<div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;          <span class="keyword">const</span> <span class="keywordtype">float</span> dz = p2.z - p1.z;</div>
<div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;          </div>
<div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;          <span class="keywordflow">return</span> (dx*dx + dy*dy + dz*dz);</div>
<div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;        }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a86918596b556ca1626f2a55640ae971e">&#9670;&nbsp;</a></span>findThresholdOtsu()</h2>

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          <td class="memname">int <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html">pcl::registration::CorrespondenceRejectorPoly</a>&lt; SourceT, TargetT &gt;::findThresholdOtsu </td>
          <td>(</td>
          <td class="paramtype">const std::vector&lt; int &gt; &amp;&#160;</td>
          <td class="paramname"><em>histogram</em></td><td>)</td>
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<p>Find the optimal value for binary histogram thresholding using Otsu's method </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramname">histogram</td><td>input histogram </td></tr>
  </table>
  </dd>
</dl>
<dl class="section return"><dt>返回</dt><dd>threshold value according to Otsu's criterion </dd></dl>
<div class="fragment"><div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;{</div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;  <span class="comment">// Precision</span></div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">double</span> eps = std::numeric_limits&lt;double&gt;::epsilon();</div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;  </div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;  <span class="comment">// Histogram dimension</span></div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">int</span> nbins = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (histogram.size ());</div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;  </div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;  <span class="comment">// Mean and inverse of the number of data points</span></div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;  <span class="keywordtype">double</span> mean = 0.0;</div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;  <span class="keywordtype">double</span> sum_inv = 0.0;</div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; nbins; ++i)</div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;  {</div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;    mean += <span class="keyword">static_cast&lt;</span><span class="keywordtype">double</span><span class="keyword">&gt;</span> (i * histogram[i]);</div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;    sum_inv += <span class="keyword">static_cast&lt;</span><span class="keywordtype">double</span><span class="keyword">&gt;</span> (histogram[i]);</div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;  }</div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;  sum_inv = 1.0/sum_inv;</div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;  mean *= sum_inv;</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;  </div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;  <span class="comment">// Probability and mean of class 1 (data to the left of threshold)</span></div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;  <span class="keywordtype">double</span> class_mean1 = 0.0;</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;  <span class="keywordtype">double</span> class_prob1 = 0.0;</div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;  <span class="keywordtype">double</span> class_prob2 = 1.0;</div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;  </div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;  <span class="comment">// Maximized between class variance and associated bin value</span></div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;  <span class="keywordtype">double</span> between_class_variance_max = 0.0;</div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;  <span class="keywordtype">int</span> result = 0;</div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;  </div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;  <span class="comment">// Loop over all bin values</span></div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; nbins; ++i)</div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;  {</div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;    class_mean1 *= class_prob1;</div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;    </div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;    <span class="comment">// Probability of bin i</span></div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">double</span> prob_i = <span class="keyword">static_cast&lt;</span><span class="keywordtype">double</span><span class="keyword">&gt;</span> (histogram[i]) * sum_inv;</div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;    </div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;    <span class="comment">// Class probability 1: sum of probabilities from 0 to i</span></div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;    class_prob1 += prob_i;</div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;    </div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;    <span class="comment">// Class probability 2: sum of probabilities from i+1 to nbins-1</span></div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;    class_prob2 -= prob_i;</div>
<div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;    </div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;    <span class="comment">// Avoid division by zero below</span></div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;    <span class="keywordflow">if</span> (std::min (class_prob1,class_prob2) &lt; eps || std::max (class_prob1,class_prob2) &gt; 1.0-eps)</div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;      <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;    </div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;    <span class="comment">// Class mean 1: sum of probabilities from 0 to i, weighted by bin value</span></div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;    class_mean1 = (class_mean1 + <span class="keyword">static_cast&lt;</span><span class="keywordtype">double</span><span class="keyword">&gt;</span> (i) * prob_i) / class_prob1;</div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;    </div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;    <span class="comment">// Class mean 2: sum of probabilities from i+1 to nbins-1, weighted by bin value</span></div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">double</span> class_mean2 = (mean - class_prob1*class_mean1) / class_prob2;</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;    </div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;    <span class="comment">// Between class variance</span></div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">double</span> between_class_variance = class_prob1 * class_prob2</div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;                                          * (class_mean1 - class_mean2)</div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;                                          * (class_mean1 - class_mean2);</div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;    </div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;    <span class="comment">// If between class variance is maximized, update result</span></div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;    <span class="keywordflow">if</span> (between_class_variance &gt; between_class_variance_max)</div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;    {</div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;      between_class_variance_max = between_class_variance;</div>
<div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;      result = i;</div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;    }</div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;  }</div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;  </div>
<div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;  <span class="keywordflow">return</span> (result);</div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;}</div>
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<h2 class="memtitle"><span class="permalink"><a href="#af51b83c930c0eded4255f0b125e0d264">&#9670;&nbsp;</a></span>getCardinality()</h2>

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template&lt;typename SourceT , typename TargetT &gt; </div>
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          <td class="memname">int <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html">pcl::registration::CorrespondenceRejectorPoly</a>&lt; SourceT, TargetT &gt;::getCardinality </td>
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<p>Get the polygon cardinality </p>
<dl class="section return"><dt>返回</dt><dd>polygon cardinality </dd></dl>
<div class="fragment"><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;        {</div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;          <span class="keywordflow">return</span> (<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#afa554cac284422e196653d72e502a610">cardinality_</a>);</div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;        }</div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_rejector_poly_html_afa554cac284422e196653d72e502a610"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#afa554cac284422e196653d72e502a610">pcl::registration::CorrespondenceRejectorPoly::cardinality_</a></div><div class="ttdeci">int cardinality_</div><div class="ttdoc">The polygon cardinality used during rejection</div><div class="ttdef"><b>Definition:</b> correspondence_rejection_poly.h:372</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a3b23f465b997d88b0b628e646f9dd3a3">&#9670;&nbsp;</a></span>getIterations()</h2>

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          <td class="memname">int <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html">pcl::registration::CorrespondenceRejectorPoly</a>&lt; SourceT, TargetT &gt;::getIterations </td>
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<p>Get the number of iterations </p>
<dl class="section return"><dt>返回</dt><dd>number of iterations </dd></dl>
<div class="fragment"><div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;        {</div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;          <span class="keywordflow">return</span> (<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#aed548e72f310a9fc5a31cec68bc7777a">iterations_</a>);</div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;        }</div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_rejector_poly_html_aed548e72f310a9fc5a31cec68bc7777a"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#aed548e72f310a9fc5a31cec68bc7777a">pcl::registration::CorrespondenceRejectorPoly::iterations_</a></div><div class="ttdeci">int iterations_</div><div class="ttdoc">Number of iterations to run</div><div class="ttdef"><b>Definition:</b> correspondence_rejection_poly.h:369</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#ab9dd0c9b233328c85803229009be093e">&#9670;&nbsp;</a></span>getRemainingCorrespondences()</h2>

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          <td class="memname">void <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html">pcl::registration::CorrespondenceRejectorPoly</a>&lt; SourceT, TargetT &gt;::getRemainingCorrespondences </td>
          <td>(</td>
          <td class="paramtype">const pcl::Correspondences &amp;&#160;</td>
          <td class="paramname"><em>original_correspondences</em>, </td>
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          <td class="paramtype">pcl::Correspondences &amp;&#160;</td>
          <td class="paramname"><em>remaining_correspondences</em>&#160;</td>
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<p>Get a list of valid correspondences after rejection from the original set of correspondences. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">original_correspondences</td><td>the set of initial correspondences given </td></tr>
    <tr><td class="paramdir">[out]</td><td class="paramname">remaining_correspondences</td><td>the resultant filtered set of remaining correspondences </td></tr>
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<p>实现了 <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector.html#a42fe3fe1efc3275e78833200bce2027e">pcl::registration::CorrespondenceRejector</a>.</p>
<div class="fragment"><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;{</div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;  <span class="comment">// This is reset after all the checks below</span></div>
<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;  remaining_correspondences = original_correspondences;</div>
<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;  </div>
<div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;  <span class="comment">// Check source/target</span></div>
<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a5575ac6cf13ce0c4054ba040afde56b8">input_</a>)</div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;  {</div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::registration::%s::getRemainingCorrespondences] No source was input! Returning all input correspondences.\n&quot;</span>,</div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;               <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#aa5996af869d7aaa6b8b8dc156038dd3f">getClassName</a> ().c_str ());</div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;  }</div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160; </div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#abb0f66416db785a197d534755e562f19">target_</a>)</div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;  {</div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::registration::%s::getRemainingCorrespondences] No target was input! Returning all input correspondences.\n&quot;</span>,</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;               <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#aa5996af869d7aaa6b8b8dc156038dd3f">getClassName</a> ().c_str ());</div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;  }</div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;  </div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;  <span class="comment">// Check cardinality</span></div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;  <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#afa554cac284422e196653d72e502a610">cardinality_</a> &lt; 2)</div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;  {</div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::registration::%s::getRemainingCorrespondences] Polygon cardinality too low!. Returning all input correspondences.\n&quot;</span>,</div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;               <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#aa5996af869d7aaa6b8b8dc156038dd3f">getClassName</a> ().c_str() );</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;  }</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;  </div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;  <span class="comment">// Number of input correspondences</span></div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">int</span> nr_correspondences = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (original_correspondences.size ());</div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160; </div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;  <span class="comment">// Not enough correspondences for polygonal rejections</span></div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;  <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#afa554cac284422e196653d72e502a610">cardinality_</a> &gt;= nr_correspondences)</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;  {</div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::registration::%s::getRemainingCorrespondences] Number of correspondences smaller than polygon cardinality! Returning all input correspondences.\n&quot;</span>,</div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;               <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#aa5996af869d7aaa6b8b8dc156038dd3f">getClassName</a> ().c_str() );</div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;  }</div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;  </div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;  <span class="comment">// Check similarity</span></div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;  <span class="keywordflow">if</span> (similarity_threshold_ &lt; 0.0f || similarity_threshold_ &gt; 1.0f)</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;  {</div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::registration::%s::getRemainingCorrespondences] Invalid edge length similarity - must be in [0,1]!. Returning all input correspondences.\n&quot;</span>,</div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;               <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#aa5996af869d7aaa6b8b8dc156038dd3f">getClassName</a> ().c_str() );</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;  }</div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;  </div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;  <span class="comment">// Similarity, squared</span></div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;  <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a07a4439a78a6f833ef62be904abd7742">similarity_threshold_squared_</a> = <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a34b2739826ffc25631b21fcdb20b2415">similarity_threshold_</a> * <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a34b2739826ffc25631b21fcdb20b2415">similarity_threshold_</a>;</div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160; </div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;  <span class="comment">// Initialization of result</span></div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;  remaining_correspondences.clear ();</div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;  remaining_correspondences.reserve (nr_correspondences);</div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;  </div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;  <span class="comment">// Number of times a correspondence is sampled and number of times it was accepted</span></div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;  std::vector&lt;int&gt; num_samples (nr_correspondences, 0);</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;  std::vector&lt;int&gt; num_accepted (nr_correspondences, 0);</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;  </div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;  <span class="comment">// Main loop</span></div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#aed548e72f310a9fc5a31cec68bc7777a">iterations_</a>; ++i)</div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;  {</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;    <span class="comment">// Sample cardinality_ correspondences without replacement</span></div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;    <span class="keyword">const</span> std::vector&lt;int&gt; idx = <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#adc6fa46eff68234bc35733343dce9d53">getUniqueRandomIndices</a> (nr_correspondences, <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#afa554cac284422e196653d72e502a610">cardinality_</a>);</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;    </div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;    <span class="comment">// Verify the polygon similarity</span></div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;    <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a1b0cbb221e66b90cccae29cf84a64147">thresholdPolygon</a> (original_correspondences, idx))</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;    {</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;      <span class="comment">// Increment sample counter and accept counter</span></div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#afa554cac284422e196653d72e502a610">cardinality_</a>; ++j)</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;      {</div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;        ++num_samples[ idx[j] ];</div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;        ++num_accepted[ idx[j] ];</div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;      }</div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;    }</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;    <span class="keywordflow">else</span></div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;    {</div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;      <span class="comment">// Not accepted, only increment sample counter</span></div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#afa554cac284422e196653d72e502a610">cardinality_</a>; ++j)</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;        ++num_samples[ idx[j] ];</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;    }</div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;  }</div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;  </div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;  <span class="comment">// Now calculate the acceptance rate of each correspondence</span></div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;  std::vector&lt;float&gt; accept_rate (nr_correspondences, 0.0f);</div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; nr_correspondences; ++i)</div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;  {</div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> numsi = num_samples[i];</div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;    <span class="keywordflow">if</span> (numsi == 0)</div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;      accept_rate[i] = 0.0f;</div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;    <span class="keywordflow">else</span></div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;      accept_rate[i] = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (num_accepted[i]) / <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (numsi);</div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;  }</div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;  </div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;  <span class="comment">// Compute a histogram in range [0,1] for acceptance rates</span></div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">int</span> hist_size = nr_correspondences / 2; <span class="comment">// TODO: Optimize this</span></div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;  <span class="keyword">const</span> std::vector&lt;int&gt; histogram = <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a37fe57f588ae4c5123a68de1da641e5d">computeHistogram</a> (accept_rate, 0.0f, 1.0f, hist_size);</div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;  </div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;  <span class="comment">// Find the cut point between outliers and inliers using Otsu&#39;s thresholding method</span></div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">int</span> cut_idx = <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a86918596b556ca1626f2a55640ae971e">findThresholdOtsu</a> (histogram);</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">float</span> cut = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (cut_idx) / <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (hist_size);</div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;  </div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;  <span class="comment">// Threshold</span></div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; nr_correspondences; ++i)</div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;    <span class="keywordflow">if</span> (accept_rate[i] &gt; cut)</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;      remaining_correspondences.push_back (original_correspondences[i]);</div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_rejector_poly_html_a07a4439a78a6f833ef62be904abd7742"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a07a4439a78a6f833ef62be904abd7742">pcl::registration::CorrespondenceRejectorPoly::similarity_threshold_squared_</a></div><div class="ttdeci">float similarity_threshold_squared_</div><div class="ttdoc">Squared value if similarity_threshold_, only for internal use</div><div class="ttdef"><b>Definition:</b> correspondence_rejection_poly.h:378</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_rejector_poly_html_a1b0cbb221e66b90cccae29cf84a64147"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a1b0cbb221e66b90cccae29cf84a64147">pcl::registration::CorrespondenceRejectorPoly::thresholdPolygon</a></div><div class="ttdeci">bool thresholdPolygon(const pcl::Correspondences &amp;corr, const std::vector&lt; int &gt; &amp;idx)</div><div class="ttdoc">Polygonal rejection of a single polygon, indexed by a subset of correspondences</div><div class="ttdef"><b>Definition:</b> correspondence_rejection_poly.h:219</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_rejector_poly_html_a34b2739826ffc25631b21fcdb20b2415"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a34b2739826ffc25631b21fcdb20b2415">pcl::registration::CorrespondenceRejectorPoly::similarity_threshold_</a></div><div class="ttdeci">float similarity_threshold_</div><div class="ttdoc">Lower edge length threshold in [0,1] used for verifying polygon similarities, where 1 is a perfect ma...</div><div class="ttdef"><b>Definition:</b> correspondence_rejection_poly.h:375</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_rejector_poly_html_a37fe57f588ae4c5123a68de1da641e5d"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a37fe57f588ae4c5123a68de1da641e5d">pcl::registration::CorrespondenceRejectorPoly::computeHistogram</a></div><div class="ttdeci">std::vector&lt; int &gt; computeHistogram(const std::vector&lt; float &gt; &amp;data, float lower, float upper, int bins)</div><div class="ttdoc">Compute a linear histogram. This function is equivalent to the MATLAB function histc,...</div><div class="ttdef"><b>Definition:</b> correspondence_rejection_poly.hpp:154</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_rejector_poly_html_a5575ac6cf13ce0c4054ba040afde56b8"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a5575ac6cf13ce0c4054ba040afde56b8">pcl::registration::CorrespondenceRejectorPoly::input_</a></div><div class="ttdeci">PointCloudSourceConstPtr input_</div><div class="ttdoc">The input point cloud dataset</div><div class="ttdef"><b>Definition:</b> correspondence_rejection_poly.h:363</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_rejector_poly_html_a86918596b556ca1626f2a55640ae971e"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a86918596b556ca1626f2a55640ae971e">pcl::registration::CorrespondenceRejectorPoly::findThresholdOtsu</a></div><div class="ttdeci">int findThresholdOtsu(const std::vector&lt; int &gt; &amp;histogram)</div><div class="ttdoc">Find the optimal value for binary histogram thresholding using Otsu's method</div><div class="ttdef"><b>Definition:</b> correspondence_rejection_poly.hpp:173</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_rejector_poly_html_aa5996af869d7aaa6b8b8dc156038dd3f"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#aa5996af869d7aaa6b8b8dc156038dd3f">pcl::registration::CorrespondenceRejectorPoly::getClassName</a></div><div class="ttdeci">const std::string &amp; getClassName() const</div><div class="ttdoc">Get a string representation of the name of this class.</div><div class="ttdef"><b>Definition:</b> correspondence_rejection.h:135</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_rejector_poly_html_abb0f66416db785a197d534755e562f19"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#abb0f66416db785a197d534755e562f19">pcl::registration::CorrespondenceRejectorPoly::target_</a></div><div class="ttdeci">PointCloudTargetConstPtr target_</div><div class="ttdoc">The input point cloud dataset target</div><div class="ttdef"><b>Definition:</b> correspondence_rejection_poly.h:366</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_rejector_poly_html_adc6fa46eff68234bc35733343dce9d53"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#adc6fa46eff68234bc35733343dce9d53">pcl::registration::CorrespondenceRejectorPoly::getUniqueRandomIndices</a></div><div class="ttdeci">std::vector&lt; int &gt; getUniqueRandomIndices(int n, int k)</div><div class="ttdoc">Get k unique random indices in range {0,...,n-1} (sampling without replacement)</div><div class="ttdef"><b>Definition:</b> correspondence_rejection_poly.h:277</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a5bba3105e4e30c6892b89d381f190898">&#9670;&nbsp;</a></span>getSimilarityThreshold()</h2>

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template&lt;typename SourceT , typename TargetT &gt; </div>
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          <td class="memname">float <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html">pcl::registration::CorrespondenceRejectorPoly</a>&lt; SourceT, TargetT &gt;::getSimilarityThreshold </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
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<p>Get the similarity threshold between edge lengths </p>
<dl class="section return"><dt>返回</dt><dd>similarity threshold </dd></dl>
<div class="fragment"><div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;        {</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;          <span class="keywordflow">return</span> (<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a34b2739826ffc25631b21fcdb20b2415">similarity_threshold_</a>);</div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;        }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#adc6fa46eff68234bc35733343dce9d53">&#9670;&nbsp;</a></span>getUniqueRandomIndices()</h2>

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          <td class="memname">std::vector&lt;int&gt; <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html">pcl::registration::CorrespondenceRejectorPoly</a>&lt; SourceT, TargetT &gt;::getUniqueRandomIndices </td>
          <td>(</td>
          <td class="paramtype">int&#160;</td>
          <td class="paramname"><em>n</em>, </td>
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<p>Get k unique random indices in range {0,...,n-1} (sampling without replacement) </p>
<dl class="section note"><dt>注解</dt><dd>No check is made to ensure that k &lt;= n. </dd></dl>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramname">n</td><td>upper index range, exclusive </td></tr>
    <tr><td class="paramname">k</td><td>number of unique indices to sample </td></tr>
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<dl class="section return"><dt>返回</dt><dd>k unique random indices in range {0,...,n-1} </dd></dl>
<div class="fragment"><div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;        {</div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;          <span class="comment">// Marked sampled indices and sample counter</span></div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;          std::vector&lt;bool&gt; sampled (n, <span class="keyword">false</span>);</div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;          <span class="keywordtype">int</span> samples = 0;</div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;          <span class="comment">// Resulting unique indices</span></div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;          std::vector&lt;int&gt; result;</div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;          result.reserve (k);</div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;          <span class="keywordflow">do</span></div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;          {</div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;            <span class="comment">// Pick a random index in the range</span></div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;            <span class="keyword">const</span> <span class="keywordtype">int</span> idx = (std::rand () % n);</div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;            <span class="comment">// If unique</span></div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;            <span class="keywordflow">if</span> (!sampled[idx])</div>
<div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;            {</div>
<div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;              <span class="comment">// Mark as sampled and increment result counter</span></div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;              sampled[idx] = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;              ++samples;</div>
<div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;              <span class="comment">// Store</span></div>
<div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;              result.push_back (idx);</div>
<div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;            }</div>
<div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;          }</div>
<div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;          <span class="keywordflow">while</span> (samples &lt; k);</div>
<div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;          </div>
<div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;          <span class="keywordflow">return</span> (result);</div>
<div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;        }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a7ff2c8b9c339f3a2002903445c571ebc">&#9670;&nbsp;</a></span>setCardinality()</h2>

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          <td class="memname">void <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html">pcl::registration::CorrespondenceRejectorPoly</a>&lt; SourceT, TargetT &gt;::setCardinality </td>
          <td>(</td>
          <td class="paramtype">int&#160;</td>
          <td class="paramname"><em>cardinality</em></td><td>)</td>
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<p>Set the polygon cardinality </p>
<dl class="params"><dt>参数</dt><dd>
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    <tr><td class="paramname">cardinality</td><td>polygon cardinality </td></tr>
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  </dd>
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<div class="fragment"><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;        {</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;          <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#afa554cac284422e196653d72e502a610">cardinality_</a> = cardinality;</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;        }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#ad276f9b13f87fb0a43cbaa12bc83da75">&#9670;&nbsp;</a></span>setInputCloud()</h2>

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          <td class="memname">void <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html">pcl::registration::CorrespondenceRejectorPoly</a>&lt; SourceT, TargetT &gt;::setInputCloud </td>
          <td>(</td>
          <td class="paramtype">const PointCloudSourceConstPtr &amp;&#160;</td>
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<p>Provide a source point cloud dataset (must contain XYZ data!), used to compute the correspondence distance. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">cloud</td><td>a cloud containing XYZ data </td></tr>
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  </dd>
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<div class="fragment"><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;        {</div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;          PCL_WARN (<span class="stringliteral">&quot;[pcl::registration::%s::setInputCloud] setInputCloud is deprecated. Please use setInputSource instead.\n&quot;</span>,</div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;                    <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#aa5996af869d7aaa6b8b8dc156038dd3f">getClassName</a> ().c_str ());</div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;          <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a5575ac6cf13ce0c4054ba040afde56b8">input_</a> = cloud;</div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;        }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#acc2f89f5758f9de93be9e2daa27af68b">&#9670;&nbsp;</a></span>setInputSource()</h2>

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          <td class="memname">void <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html">pcl::registration::CorrespondenceRejectorPoly</a>&lt; SourceT, TargetT &gt;::setInputSource </td>
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          <td class="paramtype">const PointCloudSourceConstPtr &amp;&#160;</td>
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<p>Provide a source point cloud dataset (must contain XYZ data!), used to compute the correspondence distance. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">cloud</td><td>a cloud containing XYZ data </td></tr>
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  </dd>
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<div class="fragment"><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;        {</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;          <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a5575ac6cf13ce0c4054ba040afde56b8">input_</a> = cloud;</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;        }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#ac1fb853163ad7d9bfb3cfa2629bc5e5e">&#9670;&nbsp;</a></span>setInputTarget()</h2>

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          <td class="memname">void <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html">pcl::registration::CorrespondenceRejectorPoly</a>&lt; SourceT, TargetT &gt;::setInputTarget </td>
          <td>(</td>
          <td class="paramtype">const PointCloudTargetConstPtr &amp;&#160;</td>
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<p>Provide a target point cloud dataset (must contain XYZ data!), used to compute the correspondence distance. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">target</td><td>a cloud containing XYZ data </td></tr>
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  </dd>
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<div class="fragment"><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;        {</div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;          <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#abb0f66416db785a197d534755e562f19">target_</a> = target;</div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;        }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a930c9e70a639fbe1d4e4228cd1dfc57b">&#9670;&nbsp;</a></span>setIterations()</h2>

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          <td class="memname">void <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html">pcl::registration::CorrespondenceRejectorPoly</a>&lt; SourceT, TargetT &gt;::setIterations </td>
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<p>Set the number of iterations </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramname">iterations</td><td>number of iterations </td></tr>
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<div class="fragment"><div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;        {</div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;          <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#aed548e72f310a9fc5a31cec68bc7777a">iterations_</a> = iterations;</div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;        }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a82e96a355a8bda9f912ac4c1a1c5dc6e">&#9670;&nbsp;</a></span>setSimilarityThreshold()</h2>

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          <td class="memname">void <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html">pcl::registration::CorrespondenceRejectorPoly</a>&lt; SourceT, TargetT &gt;::setSimilarityThreshold </td>
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          <td class="paramtype">float&#160;</td>
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<p>Set the similarity threshold in [0,1[ between edge lengths, where 1 is a perfect match </p>
<dl class="params"><dt>参数</dt><dd>
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    <tr><td class="paramname">similarity_threshold</td><td>similarity threshold </td></tr>
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<div class="fragment"><div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;        {</div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;          <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a34b2739826ffc25631b21fcdb20b2415">similarity_threshold_</a> = similarity_threshold;</div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;          <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a07a4439a78a6f833ef62be904abd7742">similarity_threshold_squared_</a> = similarity_threshold * similarity_threshold;</div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;        }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#aa6d7f1b7dfe41620829a2c957b4229e1">&#9670;&nbsp;</a></span>thresholdEdgeLength()</h2>

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          <td class="memname">bool <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html">pcl::registration::CorrespondenceRejectorPoly</a>&lt; SourceT, TargetT &gt;::thresholdEdgeLength </td>
          <td>(</td>
          <td class="paramtype">int&#160;</td>
          <td class="paramname"><em>index_query_1</em>, </td>
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          <td class="paramtype">float&#160;</td>
          <td class="paramname"><em>simsq</em>&#160;</td>
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<p><a class="el" href="classpcl_1_1_edge.html">Edge</a> length similarity thresholding </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramname">index_query_1</td><td>index of first source vertex </td></tr>
    <tr><td class="paramname">index_query_2</td><td>index of second source vertex </td></tr>
    <tr><td class="paramname">index_match_1</td><td>index of first target vertex </td></tr>
    <tr><td class="paramname">index_match_2</td><td>index of second target vertex </td></tr>
    <tr><td class="paramname">simsq</td><td>squared similarity threshold in [0,1] </td></tr>
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<dl class="section return"><dt>返回</dt><dd>true if edge length ratio is larger than or equal to threshold </dd></dl>
<div class="fragment"><div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;        {</div>
<div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;          <span class="comment">// Distance between source points</span></div>
<div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;          <span class="keyword">const</span> <span class="keywordtype">float</span> dist_src = <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a382b6d87c8e6d2d0750214abd67f26a5">computeSquaredDistance</a> ((*<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a5575ac6cf13ce0c4054ba040afde56b8">input_</a>)[index_query_1], (*<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a5575ac6cf13ce0c4054ba040afde56b8">input_</a>)[index_query_2]);</div>
<div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;          <span class="comment">// Distance between target points</span></div>
<div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;          <span class="keyword">const</span> <span class="keywordtype">float</span> dist_tgt = <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a382b6d87c8e6d2d0750214abd67f26a5">computeSquaredDistance</a> ((*<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#abb0f66416db785a197d534755e562f19">target_</a>)[index_match_1], (*<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#abb0f66416db785a197d534755e562f19">target_</a>)[index_match_2]);</div>
<div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;          <span class="comment">// Edge length similarity [0,1] where 1 is a perfect match</span></div>
<div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;          <span class="keyword">const</span> <span class="keywordtype">float</span> edge_sim = (dist_src &lt; dist_tgt ? dist_src / dist_tgt : dist_tgt / dist_src);</div>
<div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;          </div>
<div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;          <span class="keywordflow">return</span> (edge_sim &gt;= simsq);</div>
<div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;        }</div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_rejector_poly_html_a382b6d87c8e6d2d0750214abd67f26a5"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a382b6d87c8e6d2d0750214abd67f26a5">pcl::registration::CorrespondenceRejectorPoly::computeSquaredDistance</a></div><div class="ttdeci">float computeSquaredDistance(const SourceT &amp;p1, const TargetT &amp;p2)</div><div class="ttdoc">Squared Euclidean distance between two points using the members x, y and z</div><div class="ttdef"><b>Definition:</b> correspondence_rejection_poly.h:310</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a1b0cbb221e66b90cccae29cf84a64147">&#9670;&nbsp;</a></span>thresholdPolygon() <span class="overload">[1/2]</span></h2>

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          <td class="memname">bool <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html">pcl::registration::CorrespondenceRejectorPoly</a>&lt; SourceT, TargetT &gt;::thresholdPolygon </td>
          <td>(</td>
          <td class="paramtype">const pcl::Correspondences &amp;&#160;</td>
          <td class="paramname"><em>corr</em>, </td>
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<p>Polygonal rejection of a single polygon, indexed by a subset of correspondences </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramname">corr</td><td>all correspondences into <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a5575ac6cf13ce0c4054ba040afde56b8">input_</a> and <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#abb0f66416db785a197d534755e562f19">target_</a> </td></tr>
    <tr><td class="paramname">idx</td><td>sampled indices into <b>correspondences</b>, must have a size equal to <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#afa554cac284422e196653d72e502a610">cardinality_</a> </td></tr>
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<dl class="section return"><dt>返回</dt><dd>true if all edge length ratios are larger than or equal to <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a34b2739826ffc25631b21fcdb20b2415">similarity_threshold_</a> </dd></dl>
<div class="fragment"><div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;        {</div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;          <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#afa554cac284422e196653d72e502a610">cardinality_</a> == 2) <span class="comment">// Special case: when two points are considered, we only have one edge</span></div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;          {</div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;            <span class="keywordflow">return</span> (<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#aa6d7f1b7dfe41620829a2c957b4229e1">thresholdEdgeLength</a> (corr[ idx[0] ].index_query, corr[ idx[1] ].index_query,</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;                                         corr[ idx[0] ].index_match, corr[ idx[1] ].index_match,</div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;                                         <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#afa554cac284422e196653d72e502a610">cardinality_</a>));</div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;          }</div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;          <span class="keywordflow">else</span></div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;          { <span class="comment">// Otherwise check all edges</span></div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#afa554cac284422e196653d72e502a610">cardinality_</a>; ++i)</div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;              <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#aa6d7f1b7dfe41620829a2c957b4229e1">thresholdEdgeLength</a> (corr[ idx[i] ].index_query, corr[ idx[(i+1)%<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#afa554cac284422e196653d72e502a610">cardinality_</a>] ].index_query,</div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;                                        corr[ idx[i] ].index_match, corr[ idx[(i+1)%<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#afa554cac284422e196653d72e502a610">cardinality_</a>] ].index_match,</div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;                                        <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a07a4439a78a6f833ef62be904abd7742">similarity_threshold_squared_</a>))</div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;                <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;            </div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;            <span class="keywordflow">return</span> (<span class="keyword">true</span>);</div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;          }</div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;        }</div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_rejector_poly_html_aa6d7f1b7dfe41620829a2c957b4229e1"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#aa6d7f1b7dfe41620829a2c957b4229e1">pcl::registration::CorrespondenceRejectorPoly::thresholdEdgeLength</a></div><div class="ttdeci">bool thresholdEdgeLength(int index_query_1, int index_query_2, int index_match_1, int index_match_2, float simsq)</div><div class="ttdoc">Edge length similarity thresholding</div><div class="ttdef"><b>Definition:</b> correspondence_rejection_poly.h:328</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a4e889746bd0466f9b48a92a46fb39e3e">&#9670;&nbsp;</a></span>thresholdPolygon() <span class="overload">[2/2]</span></h2>

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template&lt;typename SourceT , typename TargetT &gt; </div>
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          <td class="memname">bool <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html">pcl::registration::CorrespondenceRejectorPoly</a>&lt; SourceT, TargetT &gt;::thresholdPolygon </td>
          <td>(</td>
          <td class="paramtype">const std::vector&lt; int &gt; &amp;&#160;</td>
          <td class="paramname"><em>source_indices</em>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const std::vector&lt; int &gt; &amp;&#160;</td>
          <td class="paramname"><em>target_indices</em>&#160;</td>
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          <td>)</td>
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<p>Polygonal rejection of a single polygon, indexed by two point index vectors </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramname">source_indices</td><td>indices of polygon points in <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a5575ac6cf13ce0c4054ba040afde56b8">input_</a>, must have a size equal to <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#afa554cac284422e196653d72e502a610">cardinality_</a> </td></tr>
    <tr><td class="paramname">target_indices</td><td>corresponding indices of polygon points in <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#abb0f66416db785a197d534755e562f19">target_</a>, must have a size equal to <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#afa554cac284422e196653d72e502a610">cardinality_</a> </td></tr>
  </table>
  </dd>
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<dl class="section return"><dt>返回</dt><dd>true if all edge length ratios are larger than or equal to <a class="el" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a34b2739826ffc25631b21fcdb20b2415">similarity_threshold_</a> </dd></dl>
<div class="fragment"><div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;        {</div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;          <span class="comment">// Convert indices to correspondences and an index vector pointing to each element</span></div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;          pcl::Correspondences corr (<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#afa554cac284422e196653d72e502a610">cardinality_</a>);</div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;          std::vector&lt;int&gt; idx (<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#afa554cac284422e196653d72e502a610">cardinality_</a>);</div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;          <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; <a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#afa554cac284422e196653d72e502a610">cardinality_</a>; ++i)</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;          {</div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;            corr[i].index_query = source_indices[i];</div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;            corr[i].index_match = target_indices[i];</div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;            idx[i] = i;</div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;          }</div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;          </div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;          <span class="keywordflow">return</span> (<a class="code" href="classpcl_1_1registration_1_1_correspondence_rejector_poly.html#a1b0cbb221e66b90cccae29cf84a64147">thresholdPolygon</a> (corr, idx));</div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;        }</div>
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<hr/>该类的文档由以下文件生成:<ul>
<li>registration/include/pcl/registration/<a class="el" href="correspondence__rejection__poly_8h_source.html">correspondence_rejection_poly.h</a></li>
<li>registration/include/pcl/registration/impl/<a class="el" href="correspondence__rejection__poly_8hpp_source.html">correspondence_rejection_poly.hpp</a></li>
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